A rapid and online microvolume flow-through dialysis probe designed for sample preparation in the analysis of veterinary drug residues is introduced. This study addresses the need for efficient and green sample preparation methods that reduce chemical waste and reagent use. The dialysis probe integrates with liquid chromatography and mass spectrometry (LC-MS) systems, facilitating automated, high-throughput analysis. The dialysis method utilizes minimal reagent volumes per sample, significantly reducing the generation of solvent waste compared to traditional sample preparation techniques. Several veterinary drugs were spiked into tissue homogenates and analyzed to validate the probe\'s efficacy. A diagnostic sensitivity of >97% and specificity of >95% were obtained for this performance evaluation. The results demonstrated the effective removal of cellular debris and particulates, ensuring sample integrity and preventing instrument clogging. The automated dialysis probe yielded recovery rates between 27 and 77% for multiple analytes, confirming its potential to streamline veterinary drug residue analysis, while adhering to green chemistry principles. The approach highlights substantial improvements in both environmental impact and operational efficiency, presenting a viable alternative to conventional sample preparation methods in regulatory and research applications.

Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juice and apple juice products. To effectively monitor this mycotoxin, there is a need for adequate analytical methods that can reliably and efficiently determine patulin levels. In this work, we developed an automated sample preparation workflow followed by liquid chromatography-atmospheric pressure chemical ionization tandem mass spectrometry (LC-APCI-MS/MS) detection to identify and quantify patulin in a single method, further expanding testing capabilities for monitoring patulin in foods compared to traditional optical methods. Using a robotic sample preparation system, apple juice, apple cider, apple puree, apple-based baby food, applesauce, fruit rolls, and fruit jam were fortified with 13C-patulin and extracted using dichloromethane (DCM) without human intervention, followed by an LC-APCI-MS/MS analysis in negative ionization mode. The method achieved a limit of quantification of 4.0 ng/g and linearity ranging from 2 to 1000 ng/mL (r2 > 0.99). Quantitation was performed with isotope dilution using 13C-patulin as an internal standard and solvent calibration standards. Average recoveries (relative standard deviations, RSD%) in seven spike matrices were 95% (9%) at 10 ng/g, 110% (5%) at 50 ng/g, 101% (7%) at 200 ng/g, and 104% (4%) at 1000 ng/g (n = 28). The ranges of within-matrix and between-matrix variability (RSD) were 3-8% and 4-9%, respectively. In incurred samples, the identity of patulin was further confirmed with a comparison of the information-dependent acquisition-enhanced product ion (IDA-EPI) MS/MS spectra to a reference standard. The metrological traceability of the patulin measurements in an incurred apple cider (21.1 ± 8.0 µg/g) and apple juice concentrate (56.6 ± 15.6 µg/g) was established using a certified reference material and calibration data to demonstrate data confidence intervals (k = 2, 95% confidence interval).

Bovine mastitis is an inflammation of the mammary gland, and it is the most common infectious disease in dairy cattle. Mastitis reduces milk yield and quality, costing dairy farmers millions of dollars each year. The aim of this study was to develop a point-of-need test for identifying mastitis pathogens that is field portable, cost-effective and can be used with minimal training. Using a proprietary polymer-based milk sample preparation method to rapidly extract pathogen DNA in milk samples, we demonstrated quantitative Polymerase Chain Reaction (qPCR) assays for six common bovine bacterial mastitis pathogens: Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Mycoplasma bovis and Escherichia coli. We also implemented this sample preparation method on a prototype point-of-need system in a proof-of-concept field trial to evaluate user experience. Importantly, the protype system enabled a sample-to-result turnaround time of within 70 min to quantitatively detect all six target pathogens. The key advantage of our point-of-need prototype system is being culture-independent yet providing automated milk sample preparation for molecular identification of key mastitis pathogens by non-expert users. Our point-of-need prototype system showed a good correlation to laboratory-based qPCR for target pathogen detection outcomes, thus potentially removing the need for milk samples to be transported off-site for laboratory testing. Above all, we successfully achieved our objective of developing a point-of-need biosensor technology for mastitis and increased its readiness level with industry partners towards technology commercialization.

This review provides an overview of the latest advancements and applications in multi-dimensional liquid chromatography coupled with mass spectrometry (mD-LC-MS), covering aspects such as inter-laboratory studies, digestion strategy, trapping column, and multi-level analysis. The shift from an offline to an online workflow reduces sample processing artifacts, analytical variability, analysis time, and the labor required for data acquisition. Over the past few years, this technique has demonstrated sufficient maturity for application across a diverse range of complex products. Moreover, there is potential for this strategy to evolve into an integrated process analytical technology tool for the real-time monitoring of monoclonal antibody quality. This review also identifies emerging trends, including its application to new modalities, the possibility of evaluating biological activity within the mD-LC set-up, and the consideration of multi-dimensional capillary electrophoresis as an alternative to mD-LC. As mD-LC-MS continues to evolve and integrate emerging trends, it holds the potential to shape the next generation of analytical tools, offering exciting possibilities for enhanced characterization and monitoring of complex biopharmaceutical products.

Membrane proteins are underrepresented during proteome characterizations, primarily owing to their lower solubility. Sodium dodecyl sulfate (SDS) is favored to enhance protein solubility but interferes with downstream analysis by mass spectrometry. Here, we present an improved workflow for SDS depletion using transmembrane electrophoresis (TME) while retaining a higher recovery of membrane proteins. Though higher levels of organic solvent lower proteome solubility, we found that the inclusion of 40% methanol provided optimal solubility of membrane proteins, with 86% recovery relative to extraction with SDS. Incorporating 40% methanol during the electrophoretic depletion of SDS by TME also maximized membrane protein recovery. We further report that methanol accelerates the rate of detergent removal, allowing TME to deplete SDS below 100 ppm in under 3 min. This is attributed to a three-fold elevation in the critical micelle concentration (CMC) of SDS in the presence of methanol, combined with a reduction in the SDS to protein binding ratio in methanol (0.3 g SDS/g protein). MS analysis of membrane proteins isolated from the methanol-assisted workflow revealed enhanced proteome detection, particularly for proteins whose pI contributed a minimal net charge and therefore possessed reduced solubility in a purely aqueous solvent. This protocol presents a robust approach for the preparation of membrane proteins by maximizing their solubility in MS-compatible solvents, offering a tool to advance membrane proteome characterization.

Generic extraction methods for the multi-compound pesticide analysis of food have found their solid place in laboratories. Ethyl acetate and acetonitrile extraction methods have been developed as fast and easy to handle standard multi-compound methods, both feature benefits and limitations. The direct injection to gas chromatography can be impaired by a high burden of coextracted matrix, resulting in deterioration of the chromatographic system and matrix effects, requiring frequent maintenance. Therefore, common clean-up methods, such as dispersive solid-phase extraction, freeze-out of fats, or gel permeation chromatography, have been applied in clean-up. Automated clean-up using micro-solid-phase extraction (µSPE) is a recent development with several demonstrated advantages when employed in the analysis of pesticides and other contaminants in foods extracted with acetonitrile, but it has not yet been evaluated in this application using ethyl acetate for extraction. In this study, an automated procedure using µSPE cartridges was developed and established on an x,y,z robotic sampler for the raw extract clean-up and preparation of diluted samples for injection on a GC-MS/MS system. Validation experiments for 212 pesticides, polychlorinated biphenyls, and polycyclic aromatic hydrocarbons in lettuce, avocado, raspberry, paprika, egg, and liver extracts were performed using µSPE with MgSO4, PSA, C18, and CarbonX. The performance in routine operation is briefly discussed.

Urine provides a diverse source of information related to a patient\'s health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at ≥8.35-fold change in abundance, ≥2 unique peptides and ≤1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.

An automated microextraction by packed sorbent followed by liquid chromatography-tandem mass spectrometry (MEPS-LC-MS/MS) method was developed for the determination of four endocrine disruptors-parabens, benzophenones, and synthetic phenolic antioxidants-in wastewater samples. The method utilizes a lab-made repackable MEPS device and a multi-syringe robotic platform that provides flexibility to test small quantities (2 mg) of multiple extraction phases and enables high-throughput capabilities for efficient method development. The overall performance of the MEPS procedure, including the investigation of influencing variables and the optimization of operational parameters for the robotic platform, was comprehensively studied through univariate and multivariate experiments. Under optimized conditions, the target analytes were effectively extracted from a small sample volume of 1.5 mL, with competitive detectability and analytical confidence. The limits of detection ranged from 0.15 to 0.30 ng L-1, and the intra-day and inter-day relative standard deviations were between 3 and 21%. The method\'s applicability was successfully demonstrated by determining methylparaben, propylparaben, butylated hydroxyanisole, and oxybenzone in wastewater samples collected from the São Carlos (SP, Brazil) river. Overall, the developed method proved to be a fast, sensitive, reliable, and environmentally friendly analytical tool for water quality monitoring.

An automated accelerated salting-out assisted solvent extraction (A-ASASE) was developed. This approach made full use of the advantages of both the accelerated solvent extraction (ASE) technique and salting-out assisted liquid-liquid extraction (SALLE), without any modifications at the level of the ASE machine. The A-ASASE combined an automated extraction at high temperature/pressure and an enrichment step using eco-friendly solvents (e.g., water and ethanol) in a fully integrated and simple way that required only low volumes of solvents. The A-ASASE was successfully applied to extract three stilbenoids, namely E-resveratrol, E-ε-viniferin and E-vitisin B, present in grapevine (Vitis vinifera L.) by-products as a proof-of-concept compound. First, factors affecting the yield of stelbenoids by SALLE were investigated by means of a design of experiment model (DOE). The SALLE was then incorporated into ASE. Various ASE operational parameters such as temperature and number of cycles were also investigated. The highest yield was obtained using a mixture of ethanol-water, 70:30 (v/v) at 60 °C, using three extraction cycles and with 5 min of contact each. The highest yields of stilbenoids were 5.87 ± 0.28 g kg-1 dry weight, 3.27 ± 0.72 g kg-1 dry weight and 1.81 ± 0.2 g kg-1 dry weight for resveratrol, E-ϵ-viniferin and vitisin B, respectively. The A-ASASE was then successfully applied to extract the same stilbenoids from the roots of Vitis vinifera L. These results highlight the applicability of A-ASASE methodology to the extraction and enrichment of the extract in compounds of medium-high polarity in an easy and fully automated way.